Source code for romcomma.base.definitions

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""" Type and constant definitions. """

from __future__ import annotations

from typing import *
from pathlib import Path
import numpy as np
import tensorflow as tf
import gpflow as gf
import romcomma.gpf as mf
import pandas as pd
from abc import abstractmethod


EFFECTIVELY_ZERO = 1.0E-64  #: Tolerance when testing floats for equality.


[docs] def INT() -> Type: """ The ``dtype`` of ``int`` in :ref:`romcomma.run.context.Environment`. """ return gf.config.default_int()
[docs] def FLOAT() -> Type: """ The ``dtype`` of ``float`` in :ref:`romcomma.run.context.Environment`. """ return gf.config.default_float()
# noinspection PyPep8Naming
[docs] class NP: """ Extended numpy types.""" Array = np.ndarray Tensor = np.ndarray # Generic Tensor. Tensor1 = Tensor # Second Order Tensor, tf.shape = (i,j) Tensor2 = Tensor # Second Order Tensor, tf.shape = (i,j) Vector = Tensor2 # First Order Tensor, column vector, tf.shape = (j,1) Covector = Tensor2 # First Order Tensor, row vector, tf.shape = (1,j) Matrix = Tensor2 # Second Order Tensor, tf.shape = (i,j) Tensor3 = Tensor # Third Order Tensor, tf.shape = (i,j,k). Tensor4 = Tensor # Fourth Order Tensor, tf.shape = (i,j,k,l). Tensor5 = Tensor Tensor6 = Tensor Tensor7 = Tensor Tensor8 = Tensor VectorLike = int | float | Sequence[int | float] | Array MatrixLike = VectorLike | Sequence[VectorLike] CovectorLike = MatrixLike ArrayLike = TensorLike = MatrixLike | Sequence[MatrixLike] | Sequence[Sequence[MatrixLike]]
# noinspection PyPep8Naming
[docs] class TF: """ Extended tensorflow types, and constants.""" Array = tf.Tensor Tensor = tf.Tensor # Generic Tensor. Tensor1 = Tensor # Second Order Tensor, tf.shape = (i,j) Tensor2 = Tensor # Second Order Tensor, tf.shape = (i,j) Vector = Tensor2 # First Order Tensor, column vector, tf.shape = (j,1) Covector = Tensor2 # First Order Tensor, row vector, tf.shape = (1,j) Matrix = Tensor2 # Second Order Tensor, tf.shape = (i,j) Tensor3 = Tensor # Third Order Tensor, tf.shape = (i,j,k). Tensor4 = Tensor # Fourth Order Tensor, tf.shape = (i,j,k,l). Tensor5 = Tensor Tensor6 = Tensor Tensor7 = Tensor Tensor8 = Tensor VectorLike = int | float | Sequence[int | float] | Array MatrixLike = Union[VectorLike, Sequence[VectorLike]] CovectorLike = MatrixLike ArrayLike = TensorLike = MatrixLike | Sequence[MatrixLike] | Sequence[Sequence[MatrixLike]] Slice = PairOfInts = tf.Tensor #: A slice, for indexing and marginalization. NaN: TF.Tensor = tf.constant(np.NaN, dtype=FLOAT()) #: A constant Tensor representing NaN.